| Item Type | Journal Article |
|---|---|
| Author | Chao-Yang Chen |
| Author | Dingrong Tan |
| Author | Xiangyi Meng |
| Author | Jianxi Gao |
| Abstract | It is essential to study the robustness and centrality of interdependent networks for building reliable interdependent systems. Here, we consider a nonlinear load-capacity cascading failure model on interdependent networks, where the initial load distribution is not random, as usually assumed, but determined by the influence of each node in the interdependent network. The node influence is measured by an automated entropy-weighted multi-attribute algorithm that takes into account both different centrality measures of nodes and the interdependence of node pairs, then averaging for not only the node itself but also its nearest neighbors and next-nearest neighbors. The resilience of interdependent networks under such a more practical and accurate setting is thoroughly investigated for various network parameters, as well as how nodes from different layers are coupled and the corresponding coupling strength. The results thereby can help better monitoring interdependent systems. |
| Date | 2022-11-14 |
| Language | en |
| Library Catalog | www.nature.com |
| URL | https://www.nature.com/articles/s41598-022-23430-3 |
| Accessed | 11/17/2022, 6:54:39 AM |
| Rights | 2022 The Author(s) |
| Extra | Number: 1 Publisher: Nature Publishing Group |
| Volume | 12 |
| Pages | 19465 |
| Publication | Scientific Reports |
| DOI | 10.1038/s41598-022-23430-3 |
| Issue | 1 |
| Journal Abbr | Sci Rep |
| ISSN | 2045-2322 |
| Date Added | 11/17/2022, 6:54:39 AM |
| Modified | 11/17/2022, 6:54:39 AM |
| Item Type | Journal Article |
|---|---|
| Author | Chaoyang Chen |
| Author | Yao Hu |
| Author | Xiangyi Meng |
| Author | Jinzhu Yu |
| Abstract | Power grids, due to their lack of network redundancy and structural interdependence, are particularly vulnerable to cascading failures, a phenomenon where a few failed nodes-having their loads exceeding their capacities—can trigger a widespread collapse of all nodes. Here, we extend the cascading failure (Motter-Lai) model to a more realistic perspective, where each node's load capacity is determined to be nonlinearly correlated with the node's centrality. Our analysis encompasses a range of synthetic networks featuring small-world or scale-free properties, as well as real-world network configurations like the IEEE bus systems and the US power grid. We find that fine-tuning this nonlinear relationship can significantly enhance a network's robustness against cascading failures when the network nodes are under attack. Additionally, the selection of initial nodes and the attack strategies also impact overall network robustness. Our findings offer valuable insights for improving the safety and resilience of power grids, bringing us closer to understanding cascading failures in a more realistic context. |
| Date | 2024-03 |
| Short Title | Cascading Failures in Power Grids |
| Library Catalog | IEEE Xplore |
| URL | https://ieeexplore.ieee.org/abstract/document/10525231 |
| Accessed | 5/24/2024, 10:36:23 AM |
| Rights | All rights reserved |
| Extra | Conference Name: Complex System Modeling and Simulation |
| Volume | 4 |
| Pages | 1-14 |
| Publication | Complex System Modeling and Simulation |
| DOI | 10.23919/CSMS.2023.0020 |
| Issue | 1 |
| ISSN | 2097-3705 |
| Date Added | 5/24/2024, 10:36:23 AM |
| Modified | 5/24/2024, 10:36:23 AM |
| Item Type | Journal Article |
|---|---|
| Author | Xiangyi Meng |
| Author | Jianxi Gao |
| Author | Shlomo Havlin |
| Abstract | Establishing long-distance quantum entanglement, i.e., entanglement transmission, in quantum networks (QN) is a key and timely challenge for developing efficient quantum communication. Traditional comprehension based on classical percolation assumes a necessary condition for successful entanglement transmission between any two infinitely distant nodes: they must be connected by at least a path of perfectly entangled states (singlets). Here, we relax this condition by explicitly showing that one can focus not on optimally converting singlets but on establishing concurrence—a key measure of bipartite entanglement. We thereby introduce a new statistical theory, concurrence percolation theory (ConPT), remotely analogous to classical percolation but fundamentally different, built by generalizing bond percolation in terms of “sponge-crossing” paths instead of clusters. Inspired by resistance network analysis, we determine the path connectivity by series and parallel rules and approximate higher-order rules via star-mesh transforms. Interestingly, we find that the entanglement transmission threshold predicted by ConPT is lower than the known classical-percolation-based results and is readily achievable on any series-parallel networks such as the Bethe lattice. ConPT promotes our understanding of how well quantum communication can be further systematically improved versus classical statistical predictions under the limitation of QN locality—a “quantum advantage” that is more general and efficient than expected. ConPT also shows a percolationlike universal critical behavior derived by finite-size analysis on the Bethe lattice and regular two-dimensional lattices, offering new perspectives for a theory of criticality in entanglement statistics. |
| Date | 2021-04-27 |
| Library Catalog | APS |
| URL | https://link.aps.org/doi/10.1103/PhysRevLett.126.170501 |
| Accessed | 4/27/2021, 10:29:05 AM |
| Rights | All rights reserved |
| Extra | Citation Key: conpt_mgh21 |
| Volume | 126 |
| Pages | 170501 |
| Publication | Physical Review Letters |
| DOI | 10.1103/PhysRevLett.126.170501 |
| Issue | 17 |
| Journal Abbr | Phys. Rev. Lett. |
| Date Added | 4/27/2021, 10:29:05 AM |
| Modified | 10/21/2022, 5:10:21 PM |
| Item Type | Journal Article |
|---|---|
| Author | Omar Malik |
| Author | Xiangyi Meng |
| Author | Shlomo Havlin |
| Author | Gyorgy Korniss |
| Author | Boleslaw Karol Szymanski |
| Author | Jianxi Gao |
| Abstract | Quantum networks describe communication networks that are based on quantum entanglement. A concurrence percolation theory has been recently developed to determine the required entanglement to enable communication between two distant stations in an arbitrary quantum network. Unfortunately, concurrence percolation has been calculated only for very small networks or large networks without loops. Here, we develop a set of mathematical tools for approximating the concurrence percolation threshold for unprecedented large-scale quantum networks by estimating the path-length distribution, under the assumption that all paths between a given pair of nodes have no overlap. We show that our approximate method agrees closely with analytical results from concurrence percolation theory. The numerical results we present include 2D square lattices of 2002 nodes and complex networks of up to 104 nodes. The entanglement percolation threshold of a quantum network is a crucial parameter for constructing a real-world communication network based on entanglement, and our method offers a significant speed-up for the intensive computations involved. |
| Date | 2022-07-29 |
| Language | en |
| Library Catalog | www.nature.com |
| URL | https://www.nature.com/articles/s42005-022-00958-4 |
| Accessed | 8/23/2022, 11:21:22 PM |
| Rights | 2022 The Author(s) |
| Extra | bibtex:conpt_mmhksg22 |
| Volume | 5 |
| Pages | 1-11 |
| Publication | Communications Physics |
| DOI | 10.1038/s42005-022-00958-4 |
| Issue | 1 |
| Journal Abbr | Commun. Phys. |
| ISSN | 2399-3650 |
| Date Added | 8/23/2022, 11:21:22 PM |
| Modified | 9/21/2022, 9:05:25 PM |
| Item Type | Journal Article |
|---|---|
| Author | Xiangyi Meng |
| Author | Yulong Cui |
| Author | Jianxi Gao |
| Author | Shlomo Havlin |
| Author | Andrei E. Ruckenstein |
| Abstract | The performance of distributing entanglement between two distant nodes in a large-scale quantum network (QN) of partially entangled bipartite pure states is generally benchmarked against the classical entanglement percolation (CEP) scheme. Improvements beyond CEP were only achieved by nonscalable strategies for restricted QN topologies. This paper explores and amplifies a new and more effective mapping of a QN, referred to as concurrence percolation theory (ConPT), that suggests using deterministic rather than probabilistic protocols for scalably improving on CEP across arbitrary QN topology. More precisely, we implement ConPT via a deterministic entanglement transmission (DET) scheme that is fully analogous to resistor network analysis, with the corresponding series and parallel rules represented by deterministic entanglement swapping and concentration protocols, respectively. The main contribution of this paper is to establish a powerful mathematical framework, which is applicable to arbitrary d-dimensional information carriers (qudits), that provides different natural optimality metrics in terms of generalized k-concurrences (a family of fundamental entanglement measures) for different QN topologies. In particular, we conclude that the introduced DET scheme (a) is optimal over the well-known nested repeater protocol for distilling entanglement from partially entangled qubits and (b) leads to higher success probabilities of obtaining a maximally entangled state than using CEP. The implementation of the DET scheme is experimentally feasible as tested on IBM's quantum computation platform. |
| Date | 2023-03-31 |
| Library Catalog | APS |
| URL | https://link.aps.org/doi/10.1103/PhysRevResearch.5.013225 |
| Accessed | 3/31/2023, 9:51:17 AM |
| Rights | All rights reserved |
| Extra | bibtex:det_mcghr23 |
| Volume | 5 |
| Pages | 013225 |
| Publication | Physical Review Research |
| DOI | 10.1103/PhysRevResearch.5.013225 |
| Issue | 1 |
| Journal Abbr | Phys. Rev. Res. |
| Date Added | 3/31/2023, 9:51:17 AM |
| Modified | 1/1/2024, 6:19:15 PM |
| Item Type | Journal Article |
|---|---|
| Author | Sergey V. Buldyrev |
| Author | Xiangyi Meng |
| Author | Timothy G. Reese |
| Author | Farzad Mortazavi |
| Author | Douglas L. Rosene |
| Author | H. Eugene Stanley |
| Author | Van J. Wedeen |
| Abstract | Purpose Recent observations of several preferred orientations of diffusion in deep white matter may indicate either (a) that axons in different directions are independently bundled in thick sheets and function noninteractively, or more interestingly, (b) that the axons are closely interwoven and would exhibit branching and sharp turns. This study aims to investigate whether the dependence of dMRI Q-ball signal on the interpulse time can decode the smaller-than-voxel-size brain structure, in particular, to distinguish scenarios (a) and (b). Methods High-resolution Q-ball images of a healthy brain taken with s/mm2 for 3 different values of were analyzed. The exchange of water molecules between crossing fibers was characterized by the fourth Fourier coefficient of the signal profile in the plane of crossing. To interpret the empirical results, a model consisting of differently oriented parallel sheets of cylinders was developed. Diffusion of water molecules inside and outside cylinders was simulated by the Monte Carlo method. Results Simulations predict that , agreeing with the empirical results, must increase with for large b-values, but may peak at a typical that depends on the thickness of the cylinder sheets for intermediate b-values. Thus, the thickness of axon layers in voxels with 2 predominant orientations can be detected from empirical taken at smaller b-values. Conclusion Based on the simulation results, recommendations are made on how to design a dMRI experiment with optimal b-value and range of in order to measure the thickness of axon sheets in the white matter, hence to distinguish (a) and (b). |
| Date | 2021-02-22 |
| Language | en |
| Library Catalog | Wiley Online Library |
| URL | https://onlinelibrary.wiley.com/doi/abs/10.1002/mrm.28702 |
| Accessed | 2/23/2021, 1:42:32 PM |
| Rights | © 2021 International Society for Magnetic Resonance in Medicine |
| Extra | _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrm.28702 |
| Volume | 86 |
| Pages | 429-441 |
| Publication | Magnetic Resonance in Medicine |
| DOI | 10.1002/mrm.28702 |
| Issue | 1 |
| Journal Abbr | Magn. Reson. Med. |
| ISSN | 1522-2594 |
| Date Added | 2/23/2021, 1:42:32 PM |
| Modified | 10/21/2022, 5:11:03 PM |
| Item Type | Journal Article |
|---|---|
| Author | Xiangyi Meng |
| Abstract | The Keldysh formalism is capable of describing driven-dissipative dynamics of open quantum systems as nonunitary effective field theories that are not necessarily thermodynamical, thus often exhibiting new physics. Here, we introduce a general Keldysh action that maximally obeys Weinbergian constraints, including locality, Poincaré invariance, and two “CPT” constraints: complete positivity and trace preserving as well as charge, parity, and time reversal symmetry. We find that the perturbative Lindblad term responsible for driven-dissipative dynamics introduced therein has the natural form of a double-trace deformation O2, which, in the large N limit, possibly leads to a new nonthermal conformal fixed point. This fixed point is IR when Δ<d/2 or UV when Δ>d/2 given d the dimensions of spacetime and Δ the scaling dimension of O. Such a UV fixed point being not forbidden by Weinbergian constraints may suggest its existence and even completion of itself, in contrast to the common sense that dissipation effects are always IR relevant. This observation implies that driven-dissipative dynamics is much richer than thermodynamics, differing in not only its noncompliance with thermodynamic symmetry (e.g., the fluctuation-dissipation relation) but its UV/IR relevance as well. Examples including a (0+1)−d harmonic oscillator under continuous measurement and a (4−ε)−d classic O(N) vector model with quartic interactions are studied. |
| Date | 2021-07-20 |
| Library Catalog | APS |
| URL | https://link.aps.org/doi/10.1103/PhysRevD.104.016016 |
| Accessed | 2/22/2022, 8:28:27 PM |
| Rights | All rights reserved |
| Extra | Publisher: American Physical Society |
| Volume | 104 |
| Pages | 016016 |
| Publication | Physical Review D |
| DOI | 10.1103/PhysRevD.104.016016 |
| Issue | 1 |
| Journal Abbr | Phys. Rev. D |
| Date Added | 2/22/2022, 8:28:27 PM |
| Modified | 10/21/2022, 5:10:49 PM |
| Item Type | Journal Article |
|---|---|
| Author | Xiangyi Meng |
| Author | Tong Yang |
| Abstract | Traditional machine-learning methods are inefficient in capturing chaos in nonlinear dynamical systems, especially when the time difference Δt between consecutive steps is so large that the extracted time series looks apparently random. Here, we introduce a new long-short-term-memory (LSTM)-based recurrent architecture by tensorizing the cell-state-to-state propagation therein, maintaining the long-term memory feature of LSTM, while simultaneously enhancing the learning of short-term nonlinear complexity. We stress that the global minima of training can be most efficiently reached by our tensor structure where all nonlinear terms, up to some polynomial order, are treated explicitly and weighted equally. The efficiency and generality of our architecture are systematically investigated and tested through theoretical analysis and experimental examinations. In our design, we have explicitly used two different many-body entanglement structures—matrix product states (MPS) and the multiscale entanglement renormalization ansatz (MERA)—as physics-inspired tensor decomposition techniques, from which we find that MERA generally performs better than MPS, hence conjecturing that the learnability of chaos is determined not only by the number of free parameters but also the tensor complexity—recognized as how entanglement entropy scales with varying matricization of the tensor. |
| Date | 2021-11-11 |
| Language | en |
| Library Catalog | www.mdpi.com |
| URL | https://www.mdpi.com/1099-4300/23/11/1491 |
| Accessed | 12/29/2021, 9:03:17 AM |
| Rights | http://creativecommons.org/licenses/by/3.0/ |
| Extra | bibtex:lstm_my21 |
| Volume | 23 |
| Pages | 1491 |
| Publication | Entropy |
| DOI | 10.3390/e23111491 |
| Issue | 11 |
| Date Added | 12/29/2021, 9:03:17 AM |
| Modified | 8/27/2023, 7:56:09 PM |
| Item Type | Journal Article |
|---|---|
| Author | Hao Wu |
| Author | Xiangyi Meng |
| Author | Michael M. Danziger |
| Author | Sean P. Cornelius |
| Author | Hui Tian |
| Author | Albert-László Barabási |
| Abstract | The understanding of recovery processes in power distribution grids is limited by the lack of realistic outage data, especially large-scale blackout datasets. By analyzing data from three electrical companies across the United States, we find that the recovery duration of an outage is connected with the downtime of its nearby outages and blackout intensity (defined as the peak number of outages during a blackout), but is independent of the number of customers affected. We present a cluster-based recovery framework to analytically characterize the dependence between outages, and interpret the dominant role blackout intensity plays in recovery. The recovery of blackouts is not random and has a universal pattern that is independent of the disruption cause, the post-disaster network structure, and the detailed repair strategy. Our study reveals that suppressing blackout intensity is a promising way to speed up restoration. |
| Date | 2022-11-30 |
| Language | en |
| Library Catalog | www.nature.com |
| URL | https://www.nature.com/articles/s41467-022-35104-9 |
| Accessed | 3/31/2023, 9:53:17 AM |
| Rights | 2022 The Author(s) |
| Volume | 13 |
| Pages | 7372 |
| Publication | Nature Communications |
| DOI | 10.1038/s41467-022-35104-9 |
| Issue | 1 |
| Journal Abbr | Nat Commun |
| ISSN | 2041-1723 |
| Date Added | 3/31/2023, 9:53:17 AM |
| Modified | 10/24/2023, 9:16:16 PM |
| Item Type | Journal Article |
|---|---|
| Author | Xiangyi Meng |
| Author | Onur Varol |
| Author | Albert-László Barabási |
| Abstract | References, the mechanism scientists rely on to signal previous knowledge, lately have turned into widely used and misused measures of scientific impact. Yet, when a discovery becomes common knowledge, citations suffer from obliteration by incorporation. This leads to the concept of hidden citation, representing a clear textual credit to a discovery without a reference to the publication embodying it. Here, we rely on unsupervised interpretable machine learning applied to the full text of each paper to systematically identify hidden citations. We find that for influential discoveries hidden citations outnumber citation counts, emerging regardless of publishing venue and discipline. We show that the prevalence of hidden citations is not driven by citation counts, but rather by the degree of the discourse on the topic within the text of the manuscripts, indicating that the more discussed is a discovery, the less visible it is to standard bibliometric analysis. Hidden citations indicate that bibliometric measures offer a limited perspective on quantifying the true impact of a discovery, raising the need to extract knowledge from the full text of the scientific corpus. |
| Date | 2024-05-01 |
| Library Catalog | Silverchair |
| URL | https://doi.org/10.1093/pnasnexus/pgae155 |
| Accessed | 5/24/2024, 10:37:11 AM |
| Rights | All rights reserved |
| Volume | 3 |
| Pages | pgae155 |
| Publication | PNAS Nexus |
| DOI | 10.1093/pnasnexus/pgae155 |
| Issue | 5 |
| Journal Abbr | PNAS Nexus |
| ISSN | 2752-6542 |
| Date Added | 5/24/2024, 10:37:11 AM |
| Modified | 5/24/2024, 10:37:11 AM |
| Item Type | Journal Article |
|---|---|
| Author | Xiangyi Meng |
| Author | Chengjun Wu |
| Author | Hong Guo |
| Date | 2015-11-13 |
| Library Catalog | CrossRef |
| URL | http://www.nature.com/articles/srep16357 |
| Accessed | 11/13/2015, 9:23:44 PM |
| Rights | All rights reserved |
| Extra | Citation Key: q-speed-limit_mwg15 |
| Volume | 5 |
| Pages | 16357 |
| Publication | Scientific Reports |
| DOI | 10.1038/srep16357 |
| Journal Abbr | Sci. Rep. |
| ISSN | 2045-2322 |
| Date Added | 11/13/2015, 9:23:44 PM |
| Modified | 9/21/2022, 9:18:58 PM |
| Item Type | Journal Article |
|---|---|
| Author | Xiangyi Meng |
| Author | Yang Li |
| Author | Jian-Wei Zhang |
| Author | Hong Guo |
| Author | H. Eugene Stanley |
| Abstract | Non-Markovianity may significantly speed up quantum dynamics when the system interacts strongly with an infinite large reservoir, of which the coupling spectrum should be fine-tuned. The potential benefits are evident in many dynamics schemes, especially the continuous-time quantum walk. Difficulty exists, however, in producing closed-form solutions with controllable accuracy against the complexity of memory kernels. Here, we introduce a new multiple-scale perturbation method that works on integro-differential equations for general study of memory effects in dynamical systems. We propose an open-system model in which a continuous-time quantum walk is enclosed in a non-Markovian reservoir, that naturally corresponds to an error correction algorithm scheme. By applying the multiple-scale method we show how emergence of different timescales is related to transition of system dynamics into the non-Markovian regime. We find that up to two long-term modes and two short-term modes exist in regular networks, limited by their intrinsic symmetries. In addition to the effective approximation by our perturbation method on general forms of reservoirs, the speed-up of quantum walks assisted by non-Markovianity is also confirmed, revealing the advantage of reservoir engineering in designing time-sensitive quantum algorithms. |
| Date | 2019-09-19 |
| Short Title | Multiple-scale perturbation method on integro-differential equations |
| Library Catalog | APS |
| URL | https://link.aps.org/doi/10.1103/PhysRevResearch.1.023020 |
| Accessed | 9/22/2019, 8:44:45 AM |
| Rights | All rights reserved |
| Extra | Citation Key: multi-scale_mlzgs19 |
| Volume | 1 |
| Pages | 023020 |
| Publication | Physical Review Research |
| DOI | 10.1103/PhysRevResearch.1.023020 |
| Issue | 2 |
| Journal Abbr | Phys. Rev. Research |
| Date Added | 9/22/2019, 8:44:45 AM |
| Modified | 10/21/2022, 5:11:28 PM |
| Item Type | Journal Article |
|---|---|
| Author | Jing Ma |
| Author | Xiangyi Meng |
| Author | Lidia A Braunstein |
| Abstract | One of the most effective strategies to mitigate the global spreading of a pandemic (e.g. coronavirus disease 2019) is to shut down international airports. From a network theory perspective, this is since international airports and flights, essentially playing the roles of bridge nodes and bridge links between countries as individual communities, dominate the epidemic spreading characteristics in the whole multi-community system. Among all epidemic characteristics, the peak fraction of infected, $I_{\max}$, is a decisive factor in evaluating an epidemic strategy given limited capacity of medical resources but is seldom considered in multi-community models. In this article, we study a general two-community system interconnected by a fraction $r$ of bridge nodes and its dynamic properties, especially $I_{\max}$, under the evolution of the susceptible-infected-recovered model. Comparing the characteristic time scales of different parts of the system allows us to analytically derive the asymptotic behaviour of $I_{\max}$ with $r$, as $r\rightarrow 0$, which follows different power-law relations in each regime of the phase diagram. We also detect crossovers when $I_{\max}$ changes from one power law to another, crossing different power-law regimes as driven by $r$. Our results enable a better prediction of the effectiveness of strategies acting on bridge nodes, denoted by the power-law exponent $\epsilon_I$ as in $I_{\max}\propto r^{1/\epsilon_I}$. |
| Date | 2022-06-01 |
| Library Catalog | Silverchair |
| URL | https://doi.org/10.1093/comnet/cnac021 |
| Accessed | 7/15/2022, 5:19:22 PM |
| Rights | All rights reserved |
| Extra | bibtex:crossover-sir-peak_mmb22 |
| Volume | 10 |
| Pages | cnac021 |
| Publication | Journal of Complex Networks |
| DOI | 10.1093/comnet/cnac021 |
| Issue | 3 |
| Journal Abbr | J. Complex Netw. |
| ISSN | 2051-1329 |
| Date Added | 7/15/2022, 5:19:22 PM |
| Modified | 10/21/2022, 5:08:26 PM |
| Item Type | Journal Article |
|---|---|
| Author | Xiangyi Meng |
| Author | Xinqi Hu |
| Author | Yu Tian |
| Author | Gaogao Dong |
| Author | Renaud Lambiotte |
| Author | Jianxi Gao |
| Author | Shlomo Havlin |
| Abstract | Quantum networks have experienced rapid advancements in both theoretical and experimental domains over the last decade, making it increasingly important to understand their large-scale features from the viewpoint of statistical physics. This review paper discusses a fundamental question: how can entanglement be effectively and indirectly (e.g., through intermediate nodes) distributed between distant nodes in an imperfect quantum network, where the connections are only partially entangled and subject to quantum noise? We survey recent studies addressing this issue by drawing exact or approximate mappings to percolation theory, a branch of statistical physics centered on network connectivity. Notably, we show that the classical percolation frameworks do not uniquely define the network’s indirect connectivity. This realization leads to the emergence of an alternative theory called “concurrence percolation”, which uncovers a previously unrecognized quantum advantage that emerges at large scales, suggesting that quantum networks are more resilient than initially assumed within classical percolation contexts, offering refreshing insights into future quantum network design. |
| Date | 2023-11 |
| Language | en |
| Library Catalog | www.mdpi.com |
| URL | https://www.mdpi.com/1099-4300/25/11/1564 |
| Accessed | 11/20/2023, 10:00:28 AM |
| Rights | http://creativecommons.org/licenses/by/3.0/ |
| Extra | bibtex:conpt_mhtdlgh23 |
| Volume | 25 |
| Pages | 1564 |
| Publication | Entropy |
| DOI | 10.3390/e25111564 |
| Issue | 11 |
| ISSN | 1099-4300 |
| Date Added | 11/20/2023, 10:00:28 AM |
| Modified | 1/1/2024, 1:27:34 AM |
| Item Type | Journal Article |
|---|---|
| Author | Bin Zhou |
| Author | Xiangyi Meng |
| Author | H. Eugene Stanley |
| Date | 2020-06-30 |
| Short Title | Power-law distribution of degree–degree distance |
| Library Catalog | pnas.org (Atypon) |
| URL | https://www.pnas.org/doi/10.1073/pnas.1918901117 |
| Accessed | 7/12/2022, 12:08:33 AM |
| Rights | All rights reserved |
| Extra | bibtex: degree-degree-distance_zms20 |
| Volume | 117 |
| Pages | 14812-14818 |
| Publication | Proceedings of the National Academy of Sciences |
| DOI | 10.1073/pnas.1918901117 |
| Issue | 26 |
| Journal Abbr | Proc. Natl. Acad. Sci. U.S.A. |
| Date Added | 7/12/2022, 12:08:33 AM |
| Modified | 9/21/2022, 9:18:36 PM |
| Item Type | Journal Article |
|---|---|
| Author | Xiangyi Meng |
| Author | Jian-Wei Zhang |
| Author | Hong Guo |
| Abstract | It is believed by the majority today that the efficient market hypothesis is imperfect because of market irrationality. Using the physical concepts and mathematical structures of quantum mechanics, we construct an econophysical framework for the stock market, based on which we analogously map massive numbers of single stocks into a reservoir consisting of many quantum harmonic oscillators and their stock index into a typical quantum open system—a quantum Brownian particle. In particular, the irrationality of stock transactions is quantitatively considered as the Planck constant within Heisenberg’s uncertainty relationship of quantum mechanics in an analogous manner. We analyze real stock data of Shanghai Stock Exchange of China and investigate fat-tail phenomena and non-Markovian behaviors of the stock index with the assistance of the quantum Brownian motion model, thereby interpreting and studying the limitations of the classical Brownian motion model for the efficient market hypothesis from a new perspective of quantum open system dynamics. |
| Date | 2016-06-15 |
| Library Catalog | ScienceDirect |
| URL | http://www.sciencedirect.com/science/article/pii/S0378437116001928 |
| Accessed | 4/26/2019, 3:57:56 PM |
| Rights | All rights reserved |
| Volume | 452 |
| Pages | 281-288 |
| Publication | Physica A: Statistical Mechanics and its Applications |
| DOI | 10.1016/j.physa.2016.02.026 |
| Journal Abbr | Physica A |
| ISSN | 0378-4371 |
| Date Added | 4/26/2019, 3:57:56 PM |
| Modified | 10/21/2022, 5:11:45 PM |
| Item Type | Journal Article |
|---|---|
| Author | Xiangyi Meng |
| Author | Jian-Wei Zhang |
| Author | Jingjing Xu |
| Author | Hong Guo |
| Abstract | We investigate the behaviors of stocks in daily price-limited stock markets by purposing a quantum spatial-periodic harmonic model. The stock price is considered to be oscillating and damping in a quantum spatial-periodic harmonic oscillator potential well. A complicated non-linear relation including inter-band positive correlation and intra-band negative correlation between the volatility and trading volume of a stock is numerically derived with the energy band structure of the model concerned. The effectiveness of price limit is re-examined, with some observed characteristics of price-limited stock markets in China studied by applying our quantum model. |
| Date | 2015-11-15 |
| Short Title | Quantum spatial-periodic harmonic model for daily price-limited stock markets |
| URL | http://www.sciencedirect.com/science/article/pii/S0378437115006019 |
| Rights | All rights reserved |
| Volume | 438 |
| Pages | 154-160 |
| Publication | Physica A: Statistical Mechanics and its Applications |
| DOI | 10.1016/j.physa.2015.06.041 |
| Journal Abbr | Physica A |
| ISSN | 0378-4371 |
| Date Added | 11/3/2015, 7:37:55 PM |
| Modified | 10/21/2022, 5:12:10 PM |
| Item Type | Journal Article |
|---|---|
| Author | Bin Zhou |
| Author | Sen Pei |
| Author | Lev Muchnik |
| Author | Xiangyi Meng |
| Author | Xiaoke Xu |
| Author | Alon Sela |
| Author | Shlomo Havlin |
| Author | H. Eugene Stanley |
| Abstract | In computational social science, epidemic-inspired spread models have been widely used to simulate information diffusion. However, recent empirical studies suggest that simple epidemic-like models typically fail to generate the structure of real-world diffusion trees. Such discrepancy calls for a better understanding of how information spreads from person to person in real-world social networks. Here, we analyse comprehensive diffusion records and associated social networks in three distinct online social platforms. We find that the diffusion probability along a social tie follows a power-law relationship with the numbers of disseminator’s followers and receiver’s followees. To develop a more realistic model of information diffusion, we incorporate this finding together with a heterogeneous response time into a cascade model. After adjusting for observational bias, the proposed model reproduces key structural features of real-world diffusion trees across the three platforms. Our finding provides a practical approach to designing more realistic generative models of information diffusion. |
| Date | 2020-08-28 |
| Language | en |
| Library Catalog | www.nature.com |
| URL | https://www.nature.com/articles/s41562-020-00945-1 |
| Accessed | 9/7/2022, 8:42:56 PM |
| Rights | 2020 The Author(s), under exclusive licence to Springer Nature Limited |
| Extra | Number: 11 Publisher: Nature Publishing Group |
| Volume | 4 |
| Pages | 1198-1207 |
| Publication | Nature Human Behaviour |
| DOI | 10.1038/s41562-020-00945-1 |
| Issue | 11 |
| Journal Abbr | Nat. Hum. Behav. |
| ISSN | 2397-3374 |
| Date Added | 9/7/2022, 8:42:56 PM |
| Modified | 10/21/2022, 5:09:14 PM |
| Item Type | Journal Article |
|---|---|
| Author | Chao-Yang Chen |
| Author | Yang Zhao |
| Author | Huanmei Qin |
| Author | Xiangyi Meng |
| Author | Jianxi Gao |
| Abstract | It is well known that interdependent networks are more vulnerable to cascading failure than single and isolated networks. In this report, we propose a new scheme to improve the robustness of interdependent scale-free network under degree-based deliberate attacks by adding links to enhance the connectivity of the interdependent network. Our proposal details 14 link addition strategies using two link importance functions. To verify the feasibility of the proposed strategies, we synthesize three different types of two-layer interdependent Barabási–Albert networks where nodes from each layer are, after ranked by their degrees, bijectively inter-coupled by assortative coupling (AC), disassortative coupling (DC), or random coupling (RC). We find that when the number of attacked nodes in the system is small, the harmonic closeness (HS-IDD) link addition strategy has the highest efficiency. Among them, S indicates that the information fusion method of each layer of the network is addition, IDD refers to the degree difference of network. With the increase of the attack proportion, the degree (DS-IDD) link addition efficiency gradually increases, and the effect is more obvious in DC and RC. Besides, through comparing different strategies, under DC and RC, the link addition strategy for the product is more effective than the sum-based strategy. However, under AC, this phenomenon is not obvious. The results show that our proposed approach can enhance the robustness of interdependent networks, and that our method provides a valuable reference for the control and prevention of cascading failures in existing interdependent networks. |
| Date | 2022-10-15 |
| Language | en |
| Library Catalog | ScienceDirect |
| URL | https://www.sciencedirect.com/science/article/pii/S0378437122005520 |
| Accessed | 9/7/2022, 8:41:57 PM |
| Rights | All rights reserved |
| Volume | 604 |
| Pages | 127851 |
| Publication | Physica A: Statistical Mechanics and its Applications |
| DOI | 10.1016/j.physa.2022.127851 |
| Journal Abbr | Physica A |
| ISSN | 0378-4371 |
| Date Added | 9/7/2022, 8:41:57 PM |
| Modified | 10/21/2022, 5:08:29 PM |
| Item Type | Journal Article |
|---|---|
| Author | Xiangyi Meng |
| Author | Bin Zhou |
| Abstract | Complex networks across various fields are often considered to be scale free—a statistical property usually solely characterized by a power-law distribution of the nodes’ degree k. However, this characterization is incomplete. In real-world networks, the distribution of the degree–degree distance η, a simple link-based metric of network connectivity similar to k, appears to exhibit a stronger power-law distribution than k. While offering an alternative characterization of scale-freeness, the discovery of η raises a fundamental question: do the power laws of k and η represent the same scale-freeness? To address this question, here we investigate the exact asymptotic relationship between the distributions of k and η, proving that every network with a power-law distribution of k also has a power-law distribution of η, but not vice versa. This prompts us to introduce two network models as counterexamples that have a power-law distribution of η but not k, constructed using the preferential attachment and fitness mechanisms, respectively. Both models show promising accuracy by fitting only one model parameter each when modeling real-world networks. Our findings suggest that η is a more suitable indicator of scale-freeness and can provide a deeper understanding of the universality and underlying mechanisms of scale-free networks. |
| Date | 2023-11-01 |
| Library Catalog | ScienceDirect |
| URL | https://www.sciencedirect.com/science/article/pii/S0960077923010755 |
| Accessed | 10/24/2023, 9:13:22 PM |
| Rights | All rights reserved |
| Extra | bibtex:scale-free_mz23 |
| Volume | 176 |
| Pages | 114173 |
| Publication | Chaos, Solitons & Fractals |
| DOI | 10.1016/j.chaos.2023.114173 |
| Journal Abbr | Chaos Solitons Fractals |
| ISSN | 0960-0779 |
| Date Added | 10/24/2023, 9:13:22 PM |
| Modified | 10/27/2023, 2:07:05 AM |
| Item Type | Journal Article |
|---|---|
| Author | Bin Zhou |
| Author | Petter Holme |
| Author | Zaiwu Gong |
| Author | Choujun Zhan |
| Author | Yao Huang |
| Author | Xin Lu |
| Author | Xiangyi Meng |
| Abstract | Although the origin of the fat-tail characteristic of the degree distribution in complex networks has been extensively researched, the underlying cause of the degree distribution characteristic across the complete range of degrees remains obscure. Here, we propose an evolution model that incorporates only two factors: the node’s weight, reflecting its innate attractiveness (nature), and the node’s degree, reflecting the external influences (nurture). The proposed model provides a good fit for degree distributions and degree ratio distributions of numerous real-world networks and reproduces their evolution processes. Our results indicate that the nurture factor plays a dominant role in the evolution of social networks. In contrast, the nature factor plays a dominant role in the evolution of non-social networks, suggesting that whether nodes are people determines the dominant factor influencing the evolution of real-world networks. |
| Date | 2023-11-03 |
| Language | en |
| Library Catalog | www.nature.com |
| URL | https://www.nature.com/articles/s41467-023-42856-5 |
| Accessed | 11/20/2023, 10:01:12 AM |
| Rights | 2023 The Author(s) |
| Extra | Number: 1 Publisher: Nature Publishing Group |
| Volume | 14 |
| Pages | 7031 |
| Publication | Nature Communications |
| DOI | 10.1038/s41467-023-42856-5 |
| Issue | 1 |
| Journal Abbr | Nat Commun |
| ISSN | 2041-1723 |
| Date Added | 11/20/2023, 10:01:12 AM |
| Modified | 11/20/2023, 10:01:12 AM |